Assembly of a pangenome uncovers novel non-reference unique insertion sequences in cattle highlighting their genetic diversity.

ObjectiveThe purpose of this study was to compare intended and actual yearly genetic gains for milk production and conformation traits and to investigate the simple selection criterion practiced among milk production and conformation traits during the last two decades in Japan. Learning how to utilize the information on intended and actual genetic gains during the last two decades into the genomic era is vital.MethodsGenetic superiority for each trait for four paths of selection (sires to breed bulls [SB], sires to breed cows [SC], dams to breed bulls [DB], and dams to breed cows [DC]) was estimated. Actual practiced simple selection criteria were investigated among milk production and conformation traits and relative emphasis on milk production and conformation traits was compared.ResultsSelection differentials in milk production traits were greater than those of conformation traits in all four paths of selection. Realized yearly genetic gain was less than that intended for milk production traits. Actual annual genetic gain for conformation traits was equivalent to or greater than intended. Retrospective selection weights of milk production and conformation traits were 0.73:0.27 and 0.56:0.44 for intended and realized genetic gains, respectively.ConclusionSelection was aimed more toward increasing genetic gain in milk production than toward conformation traits over the past two decades in Japan. In contrast, actual annual genetic gain for conformation traits was equivalent to or greater than intended. Balanced selection between milk production and conformation traits tended to be favored during actual selection. Each of four paths of selection (SB, SC, DB, and DC) has played an individual and important role. With shortening generation interval in the genomic era, a young sire arises before the completion of sire’s daughters’ milk production records. How to integrate these four paths of selection in the genomic era is vital.

Claw diseases and mastitis represent the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Yet, many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed. In this study, we attempted a detailed analysis of milk production and disease traits as well as their interrelationship using a sample of 34,497 50K genotyped German Holstein cows with milk production and claw and udder disease traits records. We performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, we generated GWAS summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations. The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher (between 0.27 for milk energy yield and 0.48 for fat-protein ratio). Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (-0.07). The genomic analysis revealed significant SNPs for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, we found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas we did not find significantly trait-associated SNPs for the other disease traits. Our results confirm the known genetic background of disease and milk production traits. We further detected 13 regions that harbor strong concordant effects on a trait combination of milk production and disease traits. This detailed investigation of genetic correlations reveals additional knowledge about the localization of regions with shared genetic effects on these trait complexes, which in turn enables a better understanding of the underlying biological pathways and putatively the utilization for a more precise design of breeding schemes.

Milk fatty acids are essential for many dairy product productions, while intramuscular fat (IMF) is associated with the quality of meat. The triacylglycerols (TAGs) are the major components of IMF and milk fat. Therefore, understanding the polymorphisms and genes linked to fat synthesis is important for animal production. Identifying quantitative trait loci (QTLs) and genes associated with milk and meat production traits has been the objective of various mapping studies in the last decade. Consistently, the QTLs on chromosomes 14, 15, and 9 have been found to be associated with milk and meat production traits in cattle, goat, and buffalo and sheep, respectively. Diacylglycerol O-acyltransferase 1 (DGAT1) gene has been reported on chromosomes 14, 15, and 9 in cattle, goat, and buffalo and sheep, respectively. Being a key role in fat metabolism and TAG synthesis, the DGAT1 has obtained considerable attention especially in animal milk production. In addition to milk production, DGAT1 has also been a subject of interest in animal meat production. Several polymorphisms have been documented in DGAT1 in various animal species including cattle, buffalo, goat, and sheep for their association with milk production traits. In addition, the DGAT1 has also been studied for their role in meat production traits in cattle, sheep, and goat. However, very limited studies have been conducted in cattle for association of DGAT1 with meat production traits in cattle. Moreover, not a single study reported the association of DGAT1 with meat production traits in buffalo; thus, further studies are warranted to fulfill this huge gap. Keeping in view the important role of DGAT1 in animal production, the current review article was designed to highlight the major development and new insights on DGAT1 effect on milk and meat production traits in cattle, buffalo, sheep, and goat. Moreover, we have also highlighted the possible future contributions of DGAT1 for the studied species.

Although it is ubiquitous in genomics, the current human reference genome (GRCh38) is incomplete: It is missing large sections of heterochromatic sequence, and as a singular, linear reference genome, it does not represent the full spectrum of human genetic diversity. To characterize gaps in GRCh38 and human genetic diversity, we developed an algorithm for sequence location approximation using nuclear families (ASLAN) to identify the region of origin of reads that do not align to GRCh38. Using unmapped reads and variant calls from whole-genome sequences (WGSs), ASLAN uses a maximum likelihood model to identify the most likely region of the genome that a subsequence belongs to given the distribution of the subsequence in the unmapped reads and phasings of families. Validating ASLAN on synthetic data and on reads from the alternative haplotypes in the decoy genome, ASLAN localizes >90% of 100-bp sequences with >92% accuracy and ∼1 Mb of resolution. We then ran ASLAN on 100-mers from unmapped reads from WGS from more than 700 families, and compared ASLAN localizations to alignment of the 100-mers to the recently released T2T-CHM13 assembly. We found that many unmapped reads in GRCh38 originate from telomeres and centromeres that are gaps in GRCh38. ASLAN localizations are in high concordance with T2T-CHM13 alignments, except in the centromeres of the acrocentric chromosomes. Comparing ASLAN localizations and T2T-CHM13 alignments, we identified sequences missing from T2T-CHM13 or sequences with high divergence from their aligned region in T2T-CHM13, highlighting new hotspots for genetic diversity.

Simple SummaryBeta-lactoglobulin (β-LG), prolactin (PRL), and Kappa casein (CSN3) all contribute to the determination of milk production and composition, but have not been assessed in local Awassi sheep. Therefore, our aim was to analyze the contribution of these genes in milk production and composition traits in commercial Awassi ewe population by genotyping and sequencing these genes. Our results showed the prevalence of the different variations (alleles) of the tested genes in the Awassi population, and no association among β-LG and CSN3 polymorphic genotypes and milk production, or PRL and fat%. Also, all 3 genes help determine the milk production potential of Awassi ewes and help assess milk components, and thus can be used in breeding programs to select for milk potential.A participatory animal-breeding program was applied to 9 commercial Awassi sheep flocks in Jordan. This study aimed to assess the influence of Beta-lactoglobulin (β-LG), Prolactin (PRL), and Kappa casein (CSN3) genes, genotypes and their interaction on milk production and composition traits of 167 genotyped Awassi ewes via Polymerase Chain Reaction (PCR) followed by sequencing. Allele frequencies for the two variants were 0.42 and 0.58 for β-LG, 0.82 and 0.18 for PRL, and 0.92 and 0.08 for CSN3. No association was found among β-LG and CSN3 polymorphic genotypes with milk production traits. However, ewes with PRL AA genotype showed higher milk production, β-LG AB was associated with lowest fat%, high solid not fat (SNF)%, protein%, and lactose%. β-LG BB was associated with highest milk density. PRL, β-LG, and CSN3 polymorphic genotypes were differentially associated with milk production and component traits. Furthermore, β-LG × PRL interaction showed the highest milk production and fat%; β-LG × PRL recorded the highest SNF%, protein%, lactose%, and milk density, while the PRL × CSN3 had the highest fat% and SNF%. The enhancing effects of these gene interactions can be incorporated in Awassi breeding programs to improve milk production and composition.

Nonreference sequences (NRSs) are DNA sequences present in global populations but absent in the current human reference genome. However, the extent and functional significance of NRSs in the human genomes and populations remains unclear. Here, we de novo assembled 539 genomes from five genetically divergent human populations using long-read sequencing technology, resulting in the identification of 5.1 million NRSs. These were merged into 45284 unique NRSs, with 29.7% being novel discoveries. Among these NRSs, 38.7% were common across the five populations, and 35.6% were population specific. The use of a graph-based pangenome approach allowed for the detection of 565 transcript expression quantitative trait loci on NRSs, with 426 of these being novel findings. Moreover, 26 NRS candidates displayed evidence of adaptive selection within human populations. Genes situated in close proximity to or intersecting with these candidates may be associated with metabolism and type 2 diabetes. Genome-wide association studies revealed 14 NRSs to be significantly associated with eight phenotypes. Additionally, 154 NRSs were found to be in strong linkage disequilibrium with 258 phenotype-associated SNPs in the GWAS catalogue. Our work expands the understanding of human NRSs and provides novel insights into their functions, facilitating evolutionary and biomedical researches.

<p><strong>Objective: </strong>The objective of this study was to analyze <em>CSN2</em> variants in Indonesian Friesian Holstein (FH) cow and their association with milk protein allergy and production traits.</p><p><strong>Methods: </strong>Genomic DNA was extracted from bloods of twelve Indonesian FH cow. Exon 7 of the <em>CSN2</em> was amplified using novel primer pair to produce 683 bp amplicon. The primers were 5’-ACCCCAATTTCTTAACCAAACCA-3’ as a forward primer and 5’-CATCAGAAGTTAAACAGCACAGT-3’ as a reverse primer. The PCR products were analyzed to determine the nucleotide sequence of <em>CSN2</em> using Bioedit version 7.2.5. Moreover, Hardy-Weinberg equilibrium (HWE) was calculated and one-way analysis of variance (ANOVA) was conducted to associate between <em>CSN2</em> variants and milk production traits.</p><p><strong>Results: </strong>Two polymorphisms, c.350A>C and c.516G>C, were identified in the <em>CSN2 </em>exon 7. Base substitution from adenine (A) to cytosine (C) of c.350A>C changed amino acid codon from histidine (CAU) to proline (CCU), and base substitution guanine (G) to cytosine (C) of c.516G>C changed amino acid codon from arginine (AGG) to serine (AGC). The CC genotype frequency for c.350A>C SNP was 33% and they were able to produce A2 <em>CSN2</em> variant which is favorable for preventing lactose intolerance. In addition, there were no association between c.350 A>C and c.516 G>C SNP of the <em>CSN2</em> with milk production traits.</p><p><strong>Conclusions: </strong>In conclusion, A1 and A2 variants of <em>CSN2</em> were identified in Indonesian FH population and they did not associate with milk production in Indonesian FH.</p><p> </p>

Recent advances in sequencing methods have led to major progress in the gapless assemblies of the human genome. However, until mid-2023, the complete sequence of the Y chromosome remained elusive. While only a small percentage of autosomal chromosomes were without complete sequences in the broadly used reference assembly of the human genome (GRCh38), around 50% of the chromosome Y DNA sequence was unknown. Using a sophisticated computational approach, we analyzed the presence of short inverted repeats in the current human reference genome (GRCh38) and in the Telomere-to-Telomere (T2T) assembly of chromosome Y. This analysis identified the location of the repeats in chromosome Y and highlighted their association with functionally annotated sequences. The comparison revealed notably more inverted repeats in the T2T assembly compared to GRCh38. These are located abundantly around exons and mobile elements, and, unexpectedly, also within gene annotations. The remarkable abundance of short inverted repeats around exons points to their importance in gene regulation, and their presence in regions associated with recombination suggests crucial roles in recombination processes. Interestingly, the most underestimated sequences in the T2T assembly are inverted repeats with a repeat length of 12–14, which are more than 20 times as frequent as those in the human reference genome GRCh38. These findings indicate that the number of short inverted repeats was significantly underestimated in the current human reference genome (GRCh38). These previously unidentified sites are of great bio-medicinal potential, as inverted repeats are precursors for the formation of cruciform DNA functional epitopes.

BackgroundThe current cattle reference genome assembly, a pseudo-linear sequence produced using sequences from a single Hereford cow, represents a limitation when performing genetic studies, especially when investigating the whole spectrum of genetic variations within the species. Detecting structural variations (SVs) poses significant challenges when relying solely on conventional methods of sequencing read mapping to the current bovine genome assembly.ResultsIn this study, we used long-reads (LR) and bioinformatic tools to construct a comprehensive bovine pangenome, using as a backbone the Hereford ARS-UCD1.2 reference genome assembly, and incorporating genetic diversity of 64 good quality de novo genome assemblies representing 14 French dairy and beef cattle breeds. Using a combination of complementary approaches, we explored the pangenome graph and identified 2.563 Gb of sequences common to all samples, and cumulated 0.295 Gb of variable sequences. Notably, we discovered 0.159 Gb of novel sequences not present in the current reference genome assembly. Our analysis also revealed 109,275 SVs, of which 84,612 were bi-allelic. These included 27,171 insertions and 24,592 deletions, while the remaining 32,849 SVs corresponded to alternate allele sequences defined as sequence substitutions between the reference genome and the sample sequence. Genome-wide association studies using SNPs and a panel of 221 SVs, shared between the pangenome and the EuroGMD chip, revealed well-known QTLs across the genome for the Holstein, Montbéliarde and Normande breeds. Among those, a QTL on chromosome 11 presents an SV with a highly significant effect on stature in the Holstein breed. This SV is a 6.2 kb deletion affecting the 5’UTR, first exon and part of the first intron of the MATN3 gene, suggesting a potential regulatory and coding effect.ConclusionsOur study provides new insights into the genetic diversity of 14 French dairy and beef breeds and highlights the utility of pangenome graphs in capturing structural variation. The identified SV associated with stature highlights the importance of integrating SVs into GWAS for a more comprehensive understanding of complex traits.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12711-025-01012-x.

Genetic parameters for beef and milk production in Dutch Red and White dual-purpose cattle and their implications for a breeding program

Anyone who has attempted to identify the responsible gene or mutation underlying a disease or mutant phenotype will know the importance of an accurate reference genome assembly. For complex vertebrate genomes, however, generating such an assembly is not trivial, even with new sequencing technologies. In 2007, a mid-point in the zebrafish genome sequencing project, I was asked to lead the project to completion. At that point we were faced with a highly fragmented physical assembly and lacked genetic maps of sufficient density and resolution to produce an accurate assembly. A high-quality reference genome assembly is generally made up of a large set of minimally overlapping large-insert genomic clones, each of which has been sequenced to completion, with a minimal number of gaps and with no artificially duplicated regions. These high-quality reference genome assemblies, such as the current human reference genome (http://www.genomereference.org), are essential for modern molecular genetic studies. For many species, however, only lower quality whole-genome shotgun assemblies are available. When one considers, for example, only the protein-coding genes, this quality of genome sequence is often not sufficient to determine the complete gene count or comprehensive set of accurate gene models. It is important, for the best application of the genomic information, that the reference genome be complete and accurately assembled. While high-throughput short-read sequencing using the current generation of machines will yield high quality for bacterial, and other small, genomes, it is not possible to completely and accurately assemble the large, complex genomes of vertebrates without other long-range contiguity information. Experience with the zebrafish genome [1] may provide some useful guidance for anyone embarking on a genome-sequencing project for new species with a complex genome. The human, mouse and zebrafish reference genomes were assembled using old-school approaches, where the long-range contiguity was derived from genetic or genomic mapping and not derived directly from sequencing reads or read-pairs. The maps used were accurate physical maps of overlapping genomic DNA fragments or high-resolution genetic maps with a high density of short sequence markers, but such maps are expensive and time-consuming to generate. There are some good possibilities for cheaper, easier way to generate accurate maps, but there are several issues to consider.

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society1,2. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals3,4. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome5. To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity6. Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent–child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements.

As large-scale genomic studies have progressed, it has been revealed that a single reference genome pattern cannot represent genetic diversity at the species level. While domestic animals tend to have complex routes of origin and migration, suggesting a possible omission of some population-specific sequences in the current reference genome. Conversely, the pangenome is a collection of all DNA sequences of a species that contains sequences shared by all individuals (core genome) and is also able to display sequence information unique to each individual (variable genome). The progress of pangenome research in humans, plants and domestic animals has proved that the missing genetic components and the identification of large structural variants (SVs) can be explored through pangenomic studies. Many individual specific sequences have been shown to be related to biological adaptability, phenotype and important economic traits. The maturity of technologies and methods such as third-generation sequencing, Telomere-to-telomere genomes, graphic genomes, and reference-free assembly will further promote the development of pangenome. In the future, pangenome combined with long-read data and multi-omics will help to resolve large SVs and their relationship with the main economic traits of interest in domesticated animals, providing better insights into animal domestication, evolution and breeding. In this review, we mainly discuss how pangenome analysis reveals genetic variations in domestic animals (sheep, cattle, pigs, chickens) and their impacts on phenotypes and how this can contribute to the understanding of species diversity. Additionally, we also go through potential issues and the future perspectives of pangenome research in livestock and poultry.

Genetic factors can influence the composition of milk fat and its genetic variation. The purpose of our work was to familiarize and study the structure, role, and influence of the DGAT1 (or diacylglycerol-O-acyltransferase 1) gene on goat milk production, its structure, and relationship with milk fat for further research in improving the goat selection system. The selection of goats, aimed at increasing the frequency of alleles with a positive effect on this trait, was initiated by geneticists. In general, identifying and evaluating genetic markers for milk performance traits are the initial and crucial steps for establishing a marker-assisted selection system (MAS). Thus, increasing productivity through genetic selection is a common goal for many animal breeding programs worldwide. The amount of milk, milk fat, and proteins are essential features of dairy farming. In cheese production, milk fatty acids perform a crucial technical function, as they are the main building blocks of milk fat, giving the cheese its unique taste and textural properties. Milk fatty acids are necessary for producing many dairy products, while intramuscular fat is associated with meat quality. Triacylglycerols (TAG) are the main components of intramuscular fat and milk fat. Therefore, understanding polymorphisms and genes related to fat synthesis is essential for animal husbandry. The identification of quantitative trait loci (QTL) and genes associated with milk production traits has been supported by various studies over the past decade. It was established that QTL genes on chromosomes 14, 15, and 9 are related to the properties of milk and meat production in goats. The presence of the diacylglycerol-O-acyltransferase 1 (DGAT1) gene in goat chromosomes 14, 15, and 9 has been reported. Having a key role in fat metabolism and TAG synthesis, DGAT1 genes have attracted considerable attention, especially in animal milk production. Several polymorphisms have been documented in DGAT1 in different animal species, including many cattle and small cattle, for their association with milk production traits. The critical role of the DGAT1 gene in milk fat metabolism makes it an exciting candidate for genetic variation in milk characteristics in dairy goats.

PPARGC1A gene plays an important role in the activation of various important hormone receptors and transcriptional factors involved in the regulation of adaptive thermogenesis, gluconeogenesis, fiber-type switching in skeletal muscle, mitochondrial biogenesis, and adipogenesis, regulating the reproduction and proposed as a candidate gene for milk-related traits in cattle. This study identified polymorphisms in the PPARGC1A gene in Italian Mediterranean buffaloes and their associations to milk production and quality traits (lactation length, peak milk yield, fat and protein yield, and percentage). As a result, a total of seven SNPs (g.-78A>G, g.224651G>C, g.286986G>A, g.304050G>A, g.325647G>A, g.325817T>C, and g.325997G>A) were identified by DNA pooled sequencing. Analysis of productivity traits within the genotyped animals revealed that the g.286986G>A located at intron 4 was associated with milk production traits, but the g.325817T>C had no association with milk production. Polymorphisms in g.-78A>G was associated with peak milk yield and milk yield, while g.304050G>A and g.325997 G>A were associated with both milk yield and protein percentage. Our findings suggest that polymorphisms in the buffalo PPARGC1A gene are associated with milk production traits and can be used as a candidate gene for milk traits and marker-assisted selection in the buffalo breeding program.